The success of a production company depends essentially on the speed with which market requirements are identified and implemented. Existing manufacturing facilities have to adapt to rapidly changing conditions. It must be possible to set up new units quickly and with a high level of certainty in respect of planning. The term “digital factory” encompasses increasingly comprehensive production planning, closely interlinked with product development as well as further processes and resources, such as logistics and operating materials, and even HR planning. An extremely complex planning environment results, whose functioning is essentially dependent on defined interfaces and standard data models. An overview of this field can be found for example in the book “Digitale Fabrik, Fabriksimulation für Produktionsplaner” (Digital factory, factory simulation for production planners) by Wolfgang Kühn, Karl-Hanser-Verlag Munich/Vienna, 2006. By transferring all aspects of the production unit into simulation models to the greatest possible degree, it is possible to safeguard investments at an early stage with only a short time before a production unit is set up and commissioned. One aspect is the simulation of automation systems. In WO 2004/053739 A2 a system and method are described, with which automation code is generated based on existing descriptions of a unit structure. The components of the unit are represented here by function blocks and have ports for data transmission. Signals, which are assigned to the function blocks, are transmitted by way of the ports. In known simulations automation devices are only linked at a logical level. Actual physical communication networks are not considered.
EP 1 402 325 B1 discloses a method for supporting project planning for manufacturing units. Here the manufacturing unit is mapped as a digital model containing objects. This digital model is embedded into a simulation environment for analysis. For a realistic simulation the model contains geometric data, kinematic data or control-related function blocks for example. A communication network is not mapped.
Automatic planning of network configurations is described in EP 1 624 614 A1. Complex networks are planned here in particular by breaking them down into sub-problems. With such a breakdown it is possible, even for systems with more than a thousand subscribers, to design a network in respect of its delay, cost and maximum data load constraints.